Venkata Vijay Krishna Paruchuru1, Aneeshkumar Perukilakattunirappel Sundareswaran2 & Er Akshun Chhapola3
1University of Southern Mississippi
Hattiesburg, MS 39406, US
2Cochin University of Science And Technology
Cochin, Kerala, India
3Delhi Technical University
Delhi, India
Abstract– The increasing reliance on data-intensive technologies in Warehouse Management Systems (WMS) has created serious data privacy issues, especially with the advent of strict regulations like the General Data Protection Regulation (GDPR). WMS, which are central to warehouse optimization, need to comply with changing data privacy regulations to protect sensitive customer data and maintain trust. Yet, the incorporation of GDPR into the design and functionality of WMS poses specific challenges, namely data gathering, processing, storage, and third-party transfer of data. The literature review suggests the research gap in terms of how data privacy law like GDPR impacts the design, functionality, and operational efficiency of WMS. Studies from 2015 to 2024 indicate that while GDPR has created an explosion of demand for better data security and privacy processes, the majority of WMS platforms—legacy systems in particular—are incapable of complying, especially with cross-border data flows and upholding the right to be forgotten. Furthermore, the effectiveness of privacy-by-design principles remains a challenge, requiring innovation in the realms of automation, consent management, and data anonymization. In spite of these challenges being identified, there is still limited systematic research into the long-term impact of GDPR on WMS scalability and flexibility in global supply chains. There is also a pressing need for in-depth research into how new technologies like AI and blockchain can be leveraged to meet GDPR requirements while also improving operational efficiency. This paper aims to fill these research gaps by synthesizing the literature and outlining areas of future research, thus helping organizations navigate the complex nexus of data privacy and WMS optimization.
Keywords– Warehouse Management Systems, GDPR compliance, data privacy, data anonymization, privacy-by-design, data retention, third-party data sharing, AI in WMS, cross-border data transfers, consent management, blockchain in supply chain, right to be forgotten, operational efficiency, data security.
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